class_docstr: Generate a new plot with overlapping ROC curves (roc1 + roc2)
  
  Parameters
  ----------
  a : ROC
      ROC plot
  
  b : ROC
      ROC plot
  
  Examples
  --------
  .. plot:: ../../examples/roc_add.py
  
  Notes
  -----
  .. versionadded:: 0.8.4
code: def plot(self, ax=None):
      a = self.a
      b = self.b
  
      if ax is None:
          _, ax = plt.subplots()
  
      _generate_plot_from_fpr_tpr_lists(a.fpr, a.tpr, ax, label=a.label)
  
      # mark the added curve with 2
      if b.label is not None and len(b.label) > 0:
          b_label = [label + " 2" for label in b.label]
      else:
          b_label = ["ROC curve 2"]
  
      _generate_plot_from_fpr_tpr_lists(b.fpr, b.tpr, ax, label=b_label)
  
      self.ax_ = ax
      self.figure_ = ax.figure
  
      return self
  
imports: import numpy
  import matplotlib.pyplot
  from sklearn.metrics import roc_curve, auc
  from sklearn.preprocessing import label_binarize
  from ..telemetry import SKLearnEvaluationLogger
  from ..util import is_column_vector, is_row_vector
  from sklearn_evaluation import __version__
  import json
  from pathlib import Path
  from sklearn_evaluation.plot.plot import AbstractPlot, AbstractComposedPlot
  from ploomber_core.exceptions import modify_exceptions
label_desc: Use image node_id 2 for calling the ROCAdd obj's underlying member method code with example usage: obj.plot(ax) and returns: self